5 papers
Certified but Private: Scalable Zero-Knowledge Proofs for Neural Network Guarantees
Youwei Zhong, Ben Merbaum, Timos Antonopoulos +4
With the growing deployment of machine learning models, formal guarantees of the robustness and fairness of these models have become increasingly important in safety-critical and l…
Learning Randomized Reductions
Ferhat Erata, Orr Paradise, Thanos Typaldos +4
Randomized self-reductions (RSRs) express using evaluated at random correlated points, enabling self-correcting programs, instance-hiding protocols, and applications in…
Learning How to Cube
Ferhat Erata, Sam Kouteili, Thanos Typaldos +4
Despite the effectiveness of Cube-and-Conquer (C&C) for solving challenging Boolean Satisfiability (SAT) problems, no prior work has shown that transformer-based models can learn e…
Coinductive Proofs of Regular Expression Equivalence in Zero Knowledge
John Kolesar, Shan Ali, Timos Antonopoulos +1
Zero-knowledge (ZK) protocols enable software developers to provide proofs of their programs' correctness to other parties without revealing the programs themselves. Regular expres…
Scheherazade: Evaluating Chain-of-Thought Math Reasoning in LLMs with Chain-of-Problems
Stephen Miner, Yoshiki Takashima, Simeng Han +4
Benchmarks are critical for measuring Large Language Model (LLM) reasoning capabilities. Some benchmarks have even become the de facto indicator of such capabilities. However, as L…